Batched Incremental Structure-from-Motion

	Batched Incremental Structure-from-Motion
	Cui Hainan(崔海楠); Shuhan Shen(申抒含); Gao Xiang(高翔); Hu Zhanyi(胡占义)
	2017
会议名称	International Conference on 3D Vision
会议日期	2017-10
会议地点	QingDao, China
摘要	The incremental Structure-from-Motion (SfM) technique has advanced in both robustness and accuracy, but the effi- ciency and scalability remain its key challenges. In this pa- per, we propose a novel batched incremental SfM technique to tackle these problems in a unified framework, where two iteration loops are contained. The inner loop is a tracks tri- angulation loop, where a novel tracks selection method is proposed to find a compact subset of tracks for the bundle adjustment (BA). The outer loop is a camera registration loop, where a batch of cameras are simultaneously added to alleviate the drifting risk and reduce the running times of BA. By the tracks selection and batched camera registra- tion, we find these two iteration loops converge fast. Ex- tensive experiments demonstrate that our new SfM system performs similarly or better than many of the state-of-the- art SfM systems in terms of camera calibration accuracy, while is more efficient, robust and scalable for large-scale scene reconstruction.
文献类型	会议论文
条目标识符	http://ir.ia.ac.cn/handle/173211/19771
专题	多模态人工智能系统全国重点实验室_机器人视觉
推荐引用方式 GB/T 7714	Cui Hainan,Shuhan Shen,Gao Xiang,et al. Batched Incremental Structure-from-Motion[C],2017.

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